Lennart Åqvist (1992) proposed a logical theory of legal evidence, based on the Bolding-Ekelöf of degrees of evidential strength. This paper reformulates Åqvist's model in terms of the probabilistic version of the kappa calculus. Proving its acceptability in the legal context is beyond the present scope, but the epistemological debate about Bayesian Law is clearly relevant. While the present model is a possible link to that line of inquiry, we offer some considerations about the broader picture of the potential of AI & Law in the evidentiary context. Whereas probabilistic reasoning is well-researched in AI, calculations about the threshold of persuasion in litigation, whatever their value, are just the tip of the iceberg. The bulk of the modeling desiderata is arguably elsewhere, if one is to ideally make the most of AI's distinctive contribution as envisaged for legal evidence research.
ASJC Scopus subject areas
- Artificial Intelligence